docs: def cov_error(self, comp_cov, score_metric="frobenius"):
          """Computes the covariance error vs. comp_cov.
  
          May require self.path_
  
          Parameters
          ----------
          comp_cov : array-like, shape = (n_features, n_features)
              The precision to compare with.
              This should normally be the test sample covariance/precision.
  
          scaling : bool
              If True, the squared error norm is divided by n_features.
              If False (default), the squared error norm is not rescaled.
  
          score_metric : str
              The type of norm used to compute the error between the estimated
              self.precision, self.covariance and the reference `comp_cov`.
              Available error types:
  
              - 'frobenius' (default): sqrt(tr(A^t.A))
              - 'spectral': sqrt(max(eigenvalues(A^t.A))
              - 'kl': kl-divergence
              - 'quadratic': quadratic loss
              - 'log_likelihood': negative log likelihood
  
          squared : bool
              Whether to compute the squared error norm or the error norm.
              If True (default), the squared error norm is returned.
              If False, the error norm is returned.
  
          Returns
          -------
          The min error between `self.covariance_` and `comp_cov`.
  
          If self.precision_ is a list, returns errors for each matrix, otherwise
          returns a scalar.
          """
          if not isinstance(self.precision_, list):
              return _compute_error(
                  comp_cov, self.covariance_, self.precision_, score_metric
              )
  
          path_errors = []
          for lidx, lam in enumerate(self.path_):
              path_errors.append(
                  _compute_error(
                      comp_cov,
                      self.covariance_[lidx],
                      self.precision_[lidx],
                      score_metric,
                  )
              )
  
          return np.array(path_errors)